U.S. Pat. No. 5,128,874 describes a system for detecting obstacles that combines an active sensor (radar) and passive sensors (cameras); the images delivered by the passive sensors are analyzed and points of interest (points of projecting relief) are extracted therefrom; for the points of interest in two successive images, the effect of rotation of the aircraft (heading, roll, pitch) during the time interval between taking the images is compensated with the help of signals delivered by an inertial navigation unit; the pairing of points of interest that are common to both images and calculating a focus of expansion corresponding to the instantaneous direction of displacement of the aircraft are then performed; the distance between the aircraft and the item corresponding to paired points of interest is calculated as a function in particular of the speed in translation of the aircraft as delivered by the inertial navigation unit; the system described in that patent is complex; in addition, the accuracy of the system is the subject of drift in the speed estimation made by the inertial unit on the basis of an acceleration measurement; furthermore, the active sensor (millimeter radar or laser) is used for detecting the presence of small obstacles ahead of the helicopter; for this purpose, the sensor performs a circular scan in order to keep the duration of acquisition down to a value that is small enough.
The time required to construct a lidar or radar image by scanning-increases in proportion to the resolution of the image (number of pixels) and with the range of the sensor. Constructing an image of 100,000 points with a laser having a range of 1500 meters (m) requires about 1 second.
During that time, the vehicle carrying the obstacle detection system can travel through a distance that is not negligible (typically of the order of 70 m for a helicopter) which has the effect of distorting the resulting image.
To compensate for such distortion, a known technique consists in using information coming from a positioning system such as a global positioning system (GPS) installed on board the carrier vehicle; this information is optionally hybridized with positioning data delivered by an inertial unit in order to individually “update” each of the measurements and construct an image that matches reality. By performing GPS and inertial unit hybridization, precision is achieved in estimating the speed of the carrier vehicle that is of the order of one centimeter per second, thus enabling very fine details to be extracted from the image; it is also necessary to be able to determine the speed of the carrier relative to the ground with sufficient accuracy in order to be able to construct a set of symbols to provide assistance in avoiding obstacles.
A drawback of that technique is that the availability and the integrity of the obstacle detection function rely on “a series connection” (in the breakdown sense), of: i) the sensor for observing the ground; ii) the system for processing images in order to detect obstacles; iii) the satellite positioning system; and iv) the inertial unit.
That solution is not sufficiently safe for a civilian application. For an “all-weather” civilian application, the role carried out by the OWS is on the contrary to add safety to the GPS, and if possible without calling on an inertial unit, which is expensive.
Thus, it is known to use an inertial navigation system (INS), a GPS receiver, or a hybrid INS/GPS system for measuring the speed of the carrier vehicle as is needed for the operation of the obstacle detector on board said vehicle.
It is also known to use a lidar scanning for any possible obstacles situated in a sector in front of the helicopter by means of a laser beam, and transmitting in real time instantaneous measurements (azimuth and elevation angles for the beam, and distance measurement or range for any echo) to a computer. The computer converts the measurements into a fixed frame of reference by using the instantaneous measurements of the Euler angles (heading, attitude) coming from an inertial measurement apparatus (IRS or AHRS) and also the speed of the carrier (from an inertial unit and where appropriate a GPS), and stores these measurements in a memory in the form of a matrix of points (or “plots”).
On the basis of these converted measurements, the computer generates a set of symbols often consisting in a view as seen from the cockpit of the scene as scanned by the scanning sensor, and does so at a rate that is high enough to ensure that it is “fluid”: although the scene being observed is generally static, the view from the cockpit is dynamic because of the movements of the carrier.
Some such systems that rely on excellent accuracy in speed measurement enable obstacle detectors to be provided that provide excellent performance; it is then possible by image processing to extract fine details such as pylons and/or high voltage electricity cables.
Nevertheless, an analysis of such systems shows that they present drawbacks, and in particular:                poor availability when using GPS on its own: in order to operate normally, GPS requires at least four satellites to be in view, and that is not necessarily true during a flight undertaken by a helicopter close to the ground, because of masking effects;        mediocre performance when using only one or more inertial units: speed accuracy is of the order of one meter per second and that does not make it possible to perform fine analysis of the image constructed from the measurements of the scanning sensor; and        high cost when using an INS solution (on its own or hybridized with a GPS).        
Known systems are unsuitable for applications in which it is desired to make safe the location function based on GPS, which means that it is imperative not to use the GPS in the OWS function in order to ensure there is no common breakdown mode.